np_shuffle

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description states 'modify a sequence in-place', which is a critical behavioral trait beyond the input schema. However, it does not disclose whether the function returns the shuffled array or None (as in numpy's shuffle). With no annotations provided, the description carries full burden, and this omission prevents a perfect score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that immediately conveys the core action. It is front-loaded with the key verb 'shuffle' and efficiently communicates the in-place nature, with no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple single-parameter tool and the presence of an output schema (which likely documents return behavior), the description is nearly complete. It lacks explicit mention of return value or side effects beyond 'in-place', but the output schema can compensate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers the 'array' parameter with a description, and the tool description adds value by specifying 'in-place' modification and 'shuffling its contents', providing context beyond the schema's parameter description alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'shuffle' and resource 'sequence', clearly stating the tool's action and in-place modification. It distinguishes itself from sibling tools like np_random_choice or np_rand, which are for generating random numbers rather than reordering an existing array.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for shuffling an array in-place, but provides no explicit guidance on when to use this tool versus alternatives like np_random_choice (which samples without replacement) or np_rand (random values). No when-not-to-use or prerequisite information is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.